setComprehensiveTemperatureGeneratorParameters function

Computes climatic and correlation information useful for creating an auto-regeressive random generation of maximum and minimun daily temparature. This function is called by ComprehensiveTemperatureGenerator.

setComprehensiveTemperatureGeneratorParameters(station, Tx_all, Tn_all,
  mean_climate_Tn = NULL, mean_climate_Tx = NULL, Tx_spline = NULL,
  Tn_spline = NULL, year_max = 1990, year_min = 1961, leap = TRUE,
  nmonth = 12, verbose = FALSE, cpf = NULL, normalize = TRUE,
  sample = NULL, option = 2, yearly = FALSE)

Arguments

• station: character vector of the IDs of the considered meteorological stations
• Tx_all: data frame containing daily maximum temperature of all meteorological station. See TEMPERATURE_MAX for formatting.
• Tn_all: data frame containing daily minimum temperature of all meteorological station. See TEMPERATURE_MIN for formatting.
• mean_climate_Tn: a matrix containing monthly mean minimum daily temperature for the considered station or an object as returned by getMonthlyMean. If NULL, it is calculated. See input of is.monthly.climate
• mean_climate_Tx: a matrix containing monthly mean maximum daily temperature for the considered station or an object as returned by getMonthlyMean. If NULL, it is calculated. See input of is.monthly.climate
• Tx_spline: daily timeseries (from the first day of year_min to the last day of year_max) of averaged maximum temperature which can be obtained by a spline interpolation of monthly mean values. Default is NULL and returned as output. See for spline interpolation utilized: splineInterpolateMonthlytoDailyforSeveralYears.
• Tn_spline: daily timeseries (from the first day of year_min to the last day of year_max) of averaged minimum temperature which can be obtained by a spline interpolation of monthly mean values. Default is NULL and returned as output. See for spline interpolation utilized: splineInterpolateMonthlytoDailyforSeveralYears.
• year_max: start year of the recorded (calibration) period
• year_min: end year of the recorded (calibration) period
• leap: logical variables. It is TRUE (Default) if leap years are considered
• nmonth: number of months in one year. Default is 12.
• verbose: logical variable
• cpf: see normalizeGaussian_severalstations
• normalize: logical variable If TRUE normalizeGaussian_severalstations is used, otherwise it is not. If option is 2, it is always TRUE.
• sample: see normalizeGaussian_severalstations
• option: integer value. If 1, the generator works with minimum and maximum temperature, if 2 (default) it works with the average value between maximum and minimum temperature and the respective daily thermal range.
• yearly: logical value. If TRUE the monthly mean values are calculated for each year from year_min to year_max separately. Default is FALSE.

Returns

This function creates and returns the following gloabal variables:

data_original matrix containing normalized and standardized data (i.e. data_original)

data_for_var matrix returned from normalizeGaussian_severalstations by processing data_original if normalize is TRUE), otherwise it is equal to data_original.

Tn_mes matrix containing measured minimum daily temperature in the analyzed time period ( $Tn_{mes}$)

Tx_mes matrix containing measured maximum daily temperature in the analyzed time period ( $Tx_{mes}$)

Tm_mes matrix calculated as to

DeltaT_mes matrix corresponding to $Tx_{mes}-Tn_{mes}$

monthly_mean_Tn matrix containing monthly means of minimum daily temperature for the considered station. It is calculated according to the input format is.monthly.climate if saveMonthlyClimate is TRUE.

monthly_mean_Tx matrix containing monthly means of maximum daily temperature for the considered station. It is calculated according to the input format is.monthly.climate if saveMonthlyClimate is TRUE.

Tx_spline matrix containing the averaged daily values of maximimum temperature obtained by a spline interpolation of the monthly climate monthly_mean_Tx or mean_climate_Tx

using splineInterpolateMonthlytoDailyforSeveralYears ( $Tx_{s}$)

Tn_spline matrix containing the averaged daily values of minimun temperature obtained by a spline interpolation of the monthly climate monthly_mean_Tn or mean_climate_Tn

using splineInterpolateMonthlytoDailyforSeveralYears ( $Tn_{s}$)

SplineAdvTm matrix calculated as $\frac{Tx_{s}+Tn_{s}}{2}$

SplineAdvDeltaT, matrix corresponding to $Tx_{s}-Tn_{s}$

stdTn vector containing the standard deviation of minimum temperature anomalies $Tn_{mes}-Tn_s$ ($\sigma_{Tn}$)

stdTx vector containing the standard deviation of maximum temperature anomalies $Tx_{mes}-Tx_s$ ($\sigma_{Tx}$)

stdTm vector containing the standard deviation of "mean" temperature anomalies $Tm_{mes}-Tm_s$ ($\sigma_{Tm}$)

Tn_mes_res standard core (standardization) of $Tn_mes$ obtained by solving column by column the expression

Tx_mes_res standard core (standardization) of $Tx_mes$ obtained by solving column-by-column the expression

Tm_mes_res standard core (standardization) of $Tm_mes$ obtained by solving column-by-column the expression

DeltaT_mes_res equal to DeltaT_mes

data_original matrix obtained as cbind(Tx_mes_res,Tn_mes_res) if option==1, or cbind(Tm_mes_res,DeltaT_mes_res) if option==2

See the R code for further details.

See Also

splineInterpolateMonthlytoDailyforSeveralYears,ComprehensiveTemperatureGenerator

Author(s)

Emanuele Cordano, Emanuele Eccel